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Reconstruction of undersampled radial PatLoc imaging using total generalized variation

Knoll, Florian, Schultz, Gerrit, Bredies, Kristian, Gallichan, Daniel, Zaitsev, Maxim, Hennig, Jürgen and Stollberger, Rudolf 2012. Reconstruction of undersampled radial PatLoc imaging using total generalized variation. Magnetic Resonance in Medicine 70 (1) , pp. 40-52. 10.1002/mrm.24426

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Abstract

In the case of radial imaging with nonlinear spatial encoding fields, a prominent star-shaped artifact has been observed if a spin distribution is encoded with an undersampled trajectory. This work presents a new iterative reconstruction method based on the total generalized variation, which reduces this artifact. For this approach, a sampling operator (as well as its adjoint) is needed that maps data from PatLoc k-space to the final image space. It is shown that this can be realized as a type-3 nonuniform fast Fourier transform, which is implemented by a combination of a type-1 and type-2 nonuniform fast Fourier transform. Using this operator, it is also possible to implement an iterative conjugate gradient SENSE based method for PatLoc reconstruction, which leads to a significant reduction of computation time in comparison to conventional PatLoc image reconstruction methods. Results from numerical simulations and in vivo PatLoc measurements with as few as 16 radial projections are presented, which demonstrate significant improvements in image quality with the total generalized variation-based approach.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Cardiff University Brain Research Imaging Centre (CUBRIC)
Engineering
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Uncontrolled Keywords: PatLoc imaging; nonlinear encoding fields; parallel imaging; radial sampling; constrained image reconstruction; total generalized variation
Publisher: John Wiley & Sons
ISSN: 0740-3194
Date of Acceptance: 29 June 2012
Last Modified: 04 Jun 2017 09:42
URI: http://orca.cf.ac.uk/id/eprint/98392

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